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2022-09-02T22:24:00.0000000Z
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Drones working to detect crop disease early, propel agricultural research forward

Phys.Org

by Addison Dehaven, South Dakota State University
Over the last decade, agriculture research has become more and more advanced—in large part because of unmanned aerial vehicles, otherwise known as drones. At South Dakota State University, drones have become integrated into a variety of research activities but have arguably been the most impactful in agricultural research.

Maitiniyazi Maimaitijiang, an assistant professor in the Department of Geography and Geospatial Sciences, has been working in conjunction with other faculty members to conduct drone-related ag research over the last few years, specifically in relation to early diagnosis of crop water stress, nutrient deficiency, crop health and diseases—major threats to food security and crop yield estimations.

"We are trying to develop robust, rapid, accurate and operational solutions and tools to detect and diagnose crop water stress, nutrient deficiency, and crop health and diseases—especially early detection," Maimaitijiang said. "We are trying to develop some new algorithms using satellites, using drones, using artificial intelligence, using different types of information, to detect this in advance before the symptoms become visible. Because once it becomes visible, the control could be too late."

Once the disease becomes visible on the leaf level, even spray may become useless, Maimaitijiang noted.

Previously, the traditional method of detecting crop disease was laborious and time consuming—requiring hours and hours of tediously collecting data over acres and acres of fields. Drone technology has created a more efficient—and reliable—method for detecting crop disease. While still not a perfect science, deep learning has made breakthroughs in the field of digital image processing, which combined with drone technology—has propelled ag research forward in recent years.

Read on: https://phys.org/news/2022-08-drones-crop-disease-early-propel.html

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